Triple

T1350818
Position Surface form Disambiguated ID Type / Status
Subject Mayan languages E28875 entity
Predicate includesLanguage P2177 FINISHED
Object Tektitek
Tektitek is a Mayan language spoken primarily by the Tektiteko people in parts of Guatemala and Mexico.
 E153798 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tektitek | Statement: [Mayan languages, includesLanguage, Tektitek]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tektitek
Context triple: [Mayan languages, includesLanguage, Tektitek]
  • A. Tigak
    Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
  • B. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
  • C. Talx
    Talx is a workforce solutions and employment verification company that operates as a subsidiary of the credit reporting agency Equifax.
  • D. Takanot
    Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
  • E. Tianeti
    Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Tektitek
Triple: [Mayan languages, includesLanguage, Tektitek]
Generated description
Tektitek is a Mayan language spoken primarily by the Tektiteko people in parts of Guatemala and Mexico.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tektitek
Target entity description: Tektitek is a Mayan language spoken primarily by the Tektiteko people in parts of Guatemala and Mexico.
  • A. Tigak
    Tigak is an Austronesian language of the Meso-Melanesian subgroup spoken primarily in parts of Papua New Guinea.
  • B. Tikkana
    Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
  • C. Talx
    Talx is a workforce solutions and employment verification company that operates as a subsidiary of the credit reporting agency Equifax.
  • D. Takanot
    Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
  • E. Tianeti
    Tianeti is a small town and administrative center in eastern Georgia, situated in the mountainous Mtskheta-Mtianeti region.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a498571d248190a0ac9eb02d97097f completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c26981d081909ca3b8d8cdf7cf2e completed March 1, 2026, 10:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc63eef908190aef058396f63a5a4 completed March 8, 2026, 12:43 a.m.
NEDg Description generation batch_69acc6dd15a481908cf870c87d469bc9 completed March 8, 2026, 12:46 a.m.
NED2 Entity disambiguation (via description) batch_69acc8072bb08190b1b7fb19fc2c0efc completed March 8, 2026, 12:51 a.m.
Created at: March 1, 2026, 7:56 p.m.